Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
Artificial intelligence (AI) is, in essence, the concept of ‘computer thinking’, encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the ‘why’), the current applications (the ‘what’), and the approach to unlocking its full potential (the ‘how’). Cite this article:
COVID-19-related patient care delays have resulted in an unprecedented patient care backlog in the field of orthopaedics. The objective of this study is to examine orthopaedic provider preferences regarding the patient care backlog and financial recovery initiatives in response to the COVID-19 pandemic. An orthopaedic research consortium at a multi-hospital tertiary care academic medical system developed a three-part survey examining provider perspectives on strategies to expand orthopaedic patient care and financial recovery. Section 1 asked for preferences regarding extending clinic hours, section 2 assessed surgeon opinions on expanding surgical opportunities, and section 3 questioned preferred strategies for departmental financial recovery. The survey was sent to the institution’s surgical and nonoperative orthopaedic providers.Aims
Methods
In 2020, the COVID-19 pandemic meant that proceeding with elective surgery was restricted to minimize exposure on wards. In order to maintain throughput of elective cases, our hospital (St Michaels Hospital, Toronto, Canada) was forced to convert as many cases as possible to same-day procedures rather than overnight admission. In this retrospective analysis, we review the cases performed as same-day arthroplasty surgeries compared to the same period in the previous 12 months. We conducted a retrospective analysis of patients undergoing total hip and knee arthroplasties over a three-month period between October and December in 2019, and again in 2020, in the middle of the COVID-19 pandemic. Patient demographics, number of outpatient primary arthroplasty cases, length of stay for admissions, 30-day readmission, and complications were collated.Aims
Methods
Open reduction in developmental dysplasia of the hip (DDH) is regularly performed despite screening programmes, due to failure of treatment or late presentation. A protocol for open reduction of DDH has been refined through collaboration between surgical, anaesthetic, and nursing teams to allow same day discharge. The objective of this study was to determine the safety and feasibility of performing open reduction of DDH as a day case. A prospectively collected departmental database was visited. All consecutive surgical cases of DDH between June 2015 and March 2020 were collected. Closed reductions, bilateral cases, cases requiring corrective osteotomy, and children with comorbidities were excluded. Data collected included demographics, safety outcome measures (blood loss, complications, readmission, reduction confirmation), and feasibility for discharge according to the Face Legs Activity Cry Consolidability (FLACC) pain scale. A satisfaction questionnaire was filled by the carers. Descriptive statistics were used for analysis.Aims
Methods
The aim of this study was to report our experience at 3.5 years with outpatient total hip arthroplasty (THA). In this prospective cohort study, we included all patients who were planned to receive primary THA through the anterior approach between 1 April 2014 and 1 October 2017. Patient-related data and surgical information were recorded. Patient reported outcome measures (PROMs) related to the hip and an anchor question were taken preoperatively, at six weeks, three months, and one year after surgery. All complications, readmissions, and reoperations were registered.Aims
Methods
To evaluate the influence of discharge timing on 30-day complications following total knee arthroplasty (TKA). We identified patients aged 18 years or older who underwent TKA between 2005 and 2016 from the American College of Surgeons’ National Surgical Quality Improvement Program (NSQIP) database. We propensity score-matched length-of-stay (LOS) groups using all relevant covariables. We used multivariable regression to determine if the rate of complications and re-admissions differed depending on LOS.Aims
Patients and Methods
We studied the impact of direct anterior (DA) A total of 6086 consecutive patients undergoing primary total hip arthroplasty (THA) at a single institution between 2013 and 2016 were retrospectively evaluated. Data obtained from electronic patient medical records included age, sex, body mass index (BMI), medical comorbidities, surgical approach, and presence of deep PJI. There were 3053 male patients (50.1%) and 3033 female patients (49.9%). The mean age and BMI of the entire cohort was 62.7 years (18 to 102, Aims
Patients and Methods
Total knee arthroplasty (TKA) is a major orthopaedic
intervention. The length of a patient's stay has been progressively
reduced with the introduction of enhanced recovery protocols: day-case
surgery has become the ultimate challenge. This narrative review shows the potential limitations of day-case
TKA. These constraints may be social, linked to patient’s comorbidities,
or due to surgery-related adverse events (e.g. pain, post-operative
nausea and vomiting, etc.). Using patient stratification, tailored surgical techniques and
multimodal opioid-sparing analgesia, day-case TKA might be achievable
in a limited group of patients. The younger, male patient without
comorbidities and with an excellent social network around him might
be a candidate. Demographic changes, effective recovery programmes and less invasive
surgical techniques such as unicondylar knee arthroplasty, may increase
the size of the group of potential day-case patients. The cost reduction achieved by day-case TKA needs to be balanced
against any increase in morbidity and mortality and the cost of
advanced follow-up at a distance with new technology. These factors
need to be evaluated before adopting this ultimate ‘fast-track’
approach. Cite this article:
Patient function after arthroplasty should ideally quickly improve.
It is not known which peri-operative function assessments predict
length of stay (LOS) and short-term functional recovery. The objective
of this study was to identify peri-operative functions assessments
predictive of hospital LOS and short-term function after hospital discharge
in hip or knee arthroplasty patients. In total, 108 patients were assessed peri-operatively with the
timed-up-and-go (TUG), Iowa level of assistance scale, post-operative
quality of recovery scale, readiness for hospital discharge scale,
and the Western Ontario and McMaster Osteoarthritis Index (WOMAC).
The older Americans resources and services activities of daily living
(ADL) questionnaire (OARS) was used to assess function two weeks
after discharge. Objectives
Methods
